---
title: "Yuanxiang Wang — author profile and papers in our library"
description: "Yuanxiang Wang, University of Chinese Academy of Sciences: 2 papers on Elamur Research (2026), h-index 1 — affiliations, topics…"
canonical: "https://research.elamur.ai/free/en/authors/yuanxiang-wang/"
---
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# Yuanxiang Wang

Yuanxiang Wang has 2 papers in our library, in 2026, most of them on [Information retrieval & search](https://md.research.elamur.ai/free/en/topics/information-retrieval/), [Bias, fairness & safety](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/), [Vision & language](https://md.research.elamur.ai/free/en/topics/multimodal/); often with [Bingkang Shi](https://md.research.elamur.ai/free/en/authors/bingkang-shi/), [Hongzhu Yi](https://md.research.elamur.ai/free/en/authors/hongzhu-yi/), [Tianyu Zong](https://md.research.elamur.ai/free/en/authors/tianyu-zong/).

2 papers in our library · 2026

[OpenAlex](https://openalex.org/A5139804461) · [**h-index 1**](https://openalex.org/authors/A5139804461) · [3 works](https://openalex.org/works?filter=author.id:A5139804461) · [1 citations](https://openalex.org/works?filter=author.id:A5139804461&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/yuanxiang-wang/#papers) · [⭐ Paper Stars ranking: #14082](https://md.research.elamur.ai/free/en/paper-stars/page/141/#star-14082)

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Yuanxiang+Wang) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Yuanxiang+Wang) · [dblp](https://dblp.org/search?q=Yuanxiang+Wang) · [ACL Anthology](https://aclanthology.org/search/?q=Yuanxiang+Wang)

## Affiliations

[🎓**University of Chinese Academy of Sciences** Beijing · China 2026 · 3 papers*current*](https://md.research.elamur.ai/free/en/universities/university-of-chinese-academy-of-sciences/)

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

## Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 6 The field of science this work belongs to (OpenAlex fields).[Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Computer Vision and Pattern Recognition · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Safety Research · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/safety-research/) · [Social Sciences · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/) · [Sociology and Political Science · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/sociology-and-political-science/)

🧭 Topics 3 Research subjects and languages the work is about.[Bias, fairness & safety · 1 work](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/) · [Information retrieval & search · 1 work](https://md.research.elamur.ai/free/en/topics/information-retrieval/) · [Vision & language · 1 work](https://md.research.elamur.ai/free/en/topics/multimodal/)

## Works by year

### 2020s

[**2026** 2 papers](https://md.research.elamur.ai/free/en/authors/yuanxiang-wang/year/2026/)

## Papers

The most cited first (OpenAlex and our library).

1. **[FAIRGAMER: Evaluating Social Biases in LLM-Based Video Game NPCs](https://md.research.elamur.ai/free/en/papers/shi-2026-fairgamer-evaluating-social-biases-llm/)** *(2026)* LLMs increasingly drive non-player characters (NPCs) in video games, and they can carry social stereotypes into gameplay.
2. **[L2Dir: Integrating L2-Norm and Directional Alignment for Unsupervised Contrastive Representation Learning in Multimodal Retrieval](https://md.research.elamur.ai/free/en/papers/zong-2026-l2dir-integrating-l-2-norm/)** *(2026)* Contrastive training for multimodal retrieval usually relies on InfoNCE, which compares embeddings only by direction on the unit hypersphere and ignores vector length (L2-norm).

## Co-authors here

7 co-authors with a page, the most papers together first.

- [Bingkang Shi](https://md.research.elamur.ai/free/en/authors/bingkang-shi/) ×2
- [Hongzhu Yi](https://md.research.elamur.ai/free/en/authors/hongzhu-yi/) ×2
- [Tianyu Zong](https://md.research.elamur.ai/free/en/authors/tianyu-zong/) ×2
- [Jen-tse Huang](https://md.research.elamur.ai/free/en/authors/jen-tse-huang/)
- [Songlin Hu](https://md.research.elamur.ai/free/en/authors/songlin-hu/)
- [Xiangxiang Chu](https://md.research.elamur.ai/free/en/authors/xiangxiang-chu/)
- [Zhenyu Guan](https://md.research.elamur.ai/free/en/authors/zhenyu-guan/)

## Venues

Where their works here were published, the most works first, with the editions of those that have a page.

- [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/) ×2: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) ×2

Updated 2 November 2026
